Ficus glumosa Delile (Moraceae), a reputed plant that is used in herbal medicine, is of high medicinal and nutritional value in local communities primarily ascribed to its phytochemical profile. Currently, there are hardly any fine details on the chemical profiling and pharmacological evaluation of this species. In this study, the flavonoids and phenolics contents of the ethanol extracts and four extracted fractions (petroleum ether (PE), ethyl acetate (EA), n-butanol, and water) of the stem bark of Ficus glumosa were firstly quantified. Further, their antioxidant and antiproliferative potentials were also evaluated. The quantitative determination indicated that the EA and n-butanol fractions possessed the highest total flavonoids/phenolics levels of 274.05 ± 0.68 mg RE/g and 78.87 ± 0.97 mg GAE/g, respectively. Similarly, for the 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2'-azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), and ferric-reducing antioxidant power (FRAP) assays, the EA fraction exhibited high potency in both DPPH and ABTS+ scavenging activities with IC50 values of 0.23 ± 0.03 mg/mL, 0.22 ± 0.03 mg/mL, and FRAP potential of 2.81 ± 0.01 mg Fe2+/g, respectively. Furthermore, the EA fraction displayed high cytotoxicity against human lung (A549) and colon (HT-29) cancer cells. Additionally, the liquid chromatography coupled with electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) was employed in order to characterize the chemical constituents of the EA fraction of Ficus glumosa stem bark. Our findings revealed 16 compounds from the EA fraction that were possibly responsible for the strong antioxidant and anti-proliferative properties. This study provides edge-cutting background information on the exploitation of Ficus glumosa as a potential natural antioxidant and anti-cancer remedy.Significant progress has been made in single image super-resolution (SISR) based on deep convolutional neural networks (CNNs). The attention mechanism can capture important features well, and the feedback mechanism can realize the fine-tuning of the output to the input. However, they have not been reasonably applied in the existing deep learning-based SISR methods. Additionally, the results of the existing methods still have serious artifacts and edge blurring. To address these issues, we proposed an Edge-enhanced with Feedback Attention Network for image super-resolution (EFANSR), which comprises three parts. The first part is an SR reconstruction network, which adaptively learns the features of different inputs by integrating channel attention and spatial attention blocks to achieve full utilization of the features. We also introduced feedback mechanism to feed high-level information back to the input and fine-tune the input in the dense spatial and channel attention block. The second part is the edge enhancement network, which obtains a sharp edge through adaptive edge enhancement processing on the output of the first SR network. The final part merges the outputs of the first two parts to obtain the final edge-enhanced SR image. Experimental results show that our method achieves performance comparable to the state-of-the-art methods with lower complexity.Pancreatic ductal adenocarcinoma (PDA) is one of the most lethal forms of human cancer, characterized by unrestrained progression, invasiveness and treatment resistance. To date, there are limited curative options, with surgical resection as the only effective strategy, hence the urgent need to discover novel therapies. A platform of onco-immunology targets is represented by molecules that play a role in the reprogrammed cellular metabolism as one hallmark of cancer. Due to the hypoxic tumor microenvironment (TME), PDA cells display an altered glucose metabolism-resulting in its increased uptake-and a higher glycolytic rate, which leads to lactate accumulation and them acting as fuel for cancer cells. The consequent acidification of the TME results in immunosuppression, which impairs the antitumor immunity. This review analyzes the genetic background and the emerging glycolytic enzymes that are involved in tumor progression, development and metastasis, and how this represents feasible therapeutic targets to counteract PDA. In particular, as the overexpressed or mutated glycolytic enzymes stimulate both humoral and cellular immune responses, we will discuss their possible exploitation as immunological targets in anti-PDA therapeutic strategies.Cancer is one of the deadliest diseases in human history with extremely poor prognosis. Although many traditional therapeutic modalities-such as surgery, chemotherapy, and radiation therapy-have proved to be successful in inhibiting the growth of tumor cells, their side effects may vastly limited the actual benefits and patient acceptance. In this context, a nanomedicine approach for cancer therapy using functionalized nanomaterial has been gaining ground recently. https://www.selleckchem.com/products/lji308.html Considering the ability to carry various anticancer drugs and to act as a photothermal agent, the use of carbon-based nanomaterials for cancer therapy has advanced rapidly. Within those nanomaterials, reduced graphene oxide (rGO), a graphene family 2D carbon nanomaterial, emerged as a good candidate for cancer photothermal therapy due to its excellent photothermal conversion in the near infrared range, large specific surface area for drug loading, as well as functional groups for functionalization with molecules such as photosensitizers, siRNA, ligands, etc. By unique design, multifunctional nanosystems could be designed based on rGO, which are endowed with promising temperature/pH-dependent drug/gene delivery abilities for multimodal cancer therapy. This could be further augmented by additional advantages offered by functionalized rGO, such as high biocompatibility, targeted delivery, and enhanced photothermal effects. Herewith, we first provide an overview of the most effective reducing agents for rGO synthesis via chemical reduction. This was followed by in-depth review of application of functionalized rGO in different cancer treatment modalities such as chemotherapy, photothermal therapy and/or photodynamic therapy, gene therapy, chemotherapy/phototherapy, and photothermal/immunotherapy.